Contextualized visual analytics for multivariate events

For event analysis, the information from both before and after the event can be crucial in certain scenarios. By incorporating a contextualized perspective in event analysis, analysts can gain deeper insights from the events. We propose a contextualized visual analysis framework which enables the identification and interpretation of temporal patterns within and across multivariate events. The framework consists of a design of visual representation for multivariate event contexts, a data processing workflow to support the visualization, and a context-centered visual analysis system to facilitate the interactive exploration of temporal patterns. To demonstrate the applicability and effectiveness of our framework, we present case studies using real-world datasets from two different domains and an expert study conducted with experienced data analysts.

Authors

Institutions

Publication Details

Journal
Visual Informatics
Published
2025-03-22
DOI
https://doi.org/10.1016/j.visinf.2025.100234
Citations
4
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
5.10

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Contextualized visual analytics for multivariate events

Zhong-Qin Lin, Gennady Andrienko, Lei Peng, Natalia Andrienko et al.
4 citations
Visual Informatics
Data Visualization and Analytics
5.10
article

Contextualized visual analytics for multivariate events

Zhong-Qin Lin, Gennady Andrienko, Lei Peng, Natalia Andrienko, Siming Chen
article en
4 citations

Abstract

For event analysis, the information from both before and after the event can be crucial in certain scenarios. By incorporating a contextualized perspective in event analysis, analysts can gain deeper insights from the events. We propose a contextualized visual analysis framework which enables the identification and interpretation of temporal patterns within and across multivariate events. The framework consists of a design of visual representation for multivariate event contexts, a data processing workflow to support the visualization, and a context-centered visual analysis system to facilitate the interactive exploration of temporal patterns. To demonstrate the applicability and effectiveness of our framework, we present case studies using real-world datasets from two different domains and an expert study conducted with experienced data analysts.

Visual InformaticsVol. 9(2)
City, University of London (GB), Fudan University (CN), Fraunhofer Institute for Intelligent Analysis and Information Systems (DE)
National Natural Science Foundation of China, Bundesministerium für Bildung und Forschung
Openalex Percentile: Top 5%
Data Visualization and Analytics
5.10
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.